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This video was recorded at MIT World Series: Nobel Laureate Speakers. What happens when a gas is cooled to absolute zero? A...
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This video was recorded at MIT World Series: Nobel Laureate Speakers. What happens when a gas is cooled to absolute zero? A new door to the quantum world opens up because all the atoms start "marching in lockstep״, forming one giant matter wave the Bose-Einstein condensate. This was predicted by Einstein in 1925, but only realized in 1995 in laboratories at JILA in Boulder and at MIT. Since then, many properties of this mysterious form of matter have been revealed, including matter wave amplification and quantized vortices. Bose condensates have been used to realize a basic atom laser, an intense source of coherent matter waves.

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This video was recorded at MIT World Series: Nobel Laureate Speakers. The Nobel Prize-winning physicist talks about various...
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This video was recorded at MIT World Series: Nobel Laureate Speakers. The Nobel Prize-winning physicist talks about various aspects of our galaxy, and discusses new methods in astronomy and astrophysics that make possible explorations deep into the heart of the Milky Way.

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This video was recorded at 24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010. You are...
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This video was recorded at 24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010. You are invited to participate in the Twenty-Fourth Annual Conference on Neural Information Processing Systems, which is the premier scientific meeting on Neural Computation. A one-day Tutorial Program offered a choice of six two-hour tutorials by leading scientists. The topics span a wide range of subjects including Neuroscience, Learning Algorithms and Theory, Bioinformatics, Image Processing, and Data Mining. The NIPS Conference featured a single track program, with contributions from a large number of intellectual communities. Presentation topics include: Algorithms and Architectures; Applications; Brain Imaging; Cognitive Science and Artificial Intelligence; Control and Reinforcement Learning; Emerging Technologies; Learning Theory; Neuroscience; Speech and Signal Processing; and Visual Processing. There were two Posner Lectures named in honor of Ed Posner who founded NIPS. Ed worked on communications and information theory at Caltech and was an early pioneer in neural networks. He organized the first NIPS conference and workshop in Denver in 1989 and incorporated the NIPS Foundation in 1992. He was an inpiring teacher and an effective leader. His untimely death in a bicycle accident in 1993 was a great loss to our community. Posner Lecturers were Josh Tenebaum and Michael Jordan. The Poster Sessions offered high-quality posters and an opportunity for researchers to share their work and exchange ideas in a collegial setting. The majority of contributions accepted at NIPS were presented as posters. The Demonstrations enabled researchers to highlight scientific advances, systems, and technologies in ways that go beyond conventional poster presentations. It provided a unique forum for demonstrating advanced technologies — both hardware and software — and fostering the direct exchange of knowledge. Detailed information can be found at NIPS 2010 Conference homepage. Click on the picture for the videos from 2010 NIPS Spotlights. Knowledge 4 All Foundation Video Journal Volume 1Video Journal of Machine Learning Abstracts - Volume 1Video Journal of Machine Learning Abstracts - Volume 1 Richard Zemel, John Shawe-Taylor Richard Zemel, John Shawe-Taylor Click on the picture for the videos from 2010 NIPS Workshops. NIPS Workshops 2010 - WhistlerNIPS Workshops, Whistler 2010NIPS Workshops, Whistler 20103 comments

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This video was recorded at NIPS Workshops, Sierra Nevada 2011. We consider an extension of the setting of label ranking, in...
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This video was recorded at NIPS Workshops, Sierra Nevada 2011. We consider an extension of the setting of label ranking, in which the learner is allowed to make predictions in the form of partial instead of total orders. Predictions of that kind are interpreted as a partial abstention: If the learner is not sufficiently certain regarding the relative order of two alternatives, it may abstain from this decision and instead declare these alternatives as being incomparable. We propose a new method for learning to predict partial orders that improves on an existing approach, both theoretically and empirically. Our method is based on the idea of thresholding the probabilities of pairwise preferences between labels as induced by a predicted (parameterized) probability distribution on the set of all rankings.

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This video was recorded at NIPS Workshops, Sierra Nevada 2011. The talk is motivated by our recent work on a recommender...
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This video was recorded at NIPS Workshops, Sierra Nevada 2011. The talk is motivated by our recent work on a recommender system for games, videos, and music on Microsoft's Xbox Live Marketplace with over 35M users. I will discuss the challenges associated with such a task including the type of data available, the nature of the user feedback data, implicit versus explicit, and the scale of the problem. I will then describe a probabilistic graphical model that combines the prediction of pairwise and listwise preferences with ideas from matrix factorisation and contentbased recommender systems to meet some of these challenges. The new model combines ideas from two other models, TrueSkill and Matchbox, which will be reviewed. TrueSkill is a model for estimating players' skills based on outcome rankings in online games on Xbox Live, and Matchbox is a Bayesian recommender system based on mapping user/item features into a common trait space. This is joint work with Tim Salimans and Ulrich Paquet. Contributors to TrueSkill include Ralf Herbrich and Tom Minka, contributors to Matchbox include Ralf Herbrich and David Stern.

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This video was recorded at NIPS Workshops, Sierra Nevada 2011. Cosmology, at the present day, works with static catalogs...
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This video was recorded at NIPS Workshops, Sierra Nevada 2011. Cosmology, at the present day, works with static catalogs (of, say, galaxies) and point estimates of fundamental physical quantities (of, for example, two-point functions, on which most cosmological science is based). Next-generation cosmological experiments are looking for ever more subtle effects in larger and larger data sets; they will not provide all the cosmological information of which they are capable unless we can develop probabilistic approaches that transmit as best as possible all the information in the raw data to the quantities of interest (for example, the spectrum of primordial density fluctuations or the mass of the dark-matter particle). I will show some baby steps towards creating a probabilistic generative model of the full system, with cosmological parameters at the top and raw image pixels at the bottom. Parts of this work have been performed in collaboration with Fergus (NYU), Lang (Princeton), Marshall (Oxford), and Murray (Edinburgh).

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This video was recorded at NIPS Workshops, Sierra Nevada 2011. Cosmic Microwave Background (CMB) temperature anisotropies...
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This video was recorded at NIPS Workshops, Sierra Nevada 2011. Cosmic Microwave Background (CMB) temperature anisotropies and polarisation measurements have been one of the key cosmological probes to establish the current cosmological model. The ESA's PLANCK mission is designed to deliver full-sky coverage, low-noise level, high resolution temperature and polarisations maps. We will brieﬂy review some of the key problem of the PLANCK data analysis, and we will present how sparsity can be used to analyze such data set, especially for learning how to separate the CMB from other sky components.

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